The proposed method employs a deep learning technique known as conditional generative adversarial network (cGAN) to convert a noisy low-resolution TF image of a ...

The results reveal that the proposed image improvement method generates high-resolution TF representations which are better than both the traditional TF images ...

The proposed method employs a deep learning technique known as conditional generative adversarial network (cGAN) to convert a noisy low-resolution TF image ...

Connected Papers is a visual tool to help researchers and applied scientists find academic papers relevant to their field of work.

This study introduces an intelligent gear fault diagnosis system employing a convolutional neural network (CNN), utilizing vibration and thermal features.

With the input of deep learning networks as the application background, this method evaluates the time–frequency image quality of rotating machinery vibration ...

In the proposed method, deep neural networks with deep architectures are established to adaptively mine available fault characteristics and automatically ...

A deep time–frequency learning (DTFL) signal enhancement algorithm with interpretability is proposed in this paper. The DTFL constructs a deep nonlinear ...

Abstract—Time-frequency analysis is an initial step in the design of invariant representations for any type of time series signals. Time-frequency analysis ...

In this review paper, we provide a comprehensive overview of deep learning-based methods for post-processing MR images to enhance image quality and correct ...